Comments (1)
We recently released an update to deal with situations where the spark context is not available to query things like default parallelism. This should address this
In general, the way to safeguard against this is to explicitly specify the number of partitions requested when generating the specification for your dataset. This will avoid the query against the sparkContext.
While we have not tested against Spark Connect, we have tested against other environments where there is no sparkContext available
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Related Issues (20)
- Setuptools need to include required packages for working with the library locally (outside of the databricks environment) HOT 2
- Improve build ordering dependencies
- Changed interim build labelling to comply with PEP 440 HOT 1
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- Support range of values for generating array valued columns
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- Reference Previous Rows HOT 3
- Add support for constraints
- Add support for structured columns HOT 1
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- Create some pre-canned standard datasets like the h20 groupby dataset HOT 2
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